3 papers
cs.CL2024
LASER: Learning by Aligning Self-supervised Representations of Speech for Improving Content-related Tasks
Amit Meghanani, Thomas Hain
Self-supervised learning (SSL)-based speech models are extensively used for full-stack speech processing. However, it has been observed that improving SSL-based speech representati…
cs.CL2024
Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations
Amit Meghanani, Thomas Hain
Acoustic word embeddings (AWEs) are vector representations of spoken words. An effective method for obtaining AWEs is the Correspondence Auto-Encoder (CAE). In the past, the CAE me…
cs.CL2024
SCORE: Self-supervised Correspondence Fine-tuning for Improved Content Representations
Amit Meghanani, Thomas Hain
There is a growing interest in cost-effective self-supervised fine-tuning (SSFT) of self-supervised learning (SSL)-based speech models to obtain task-specific representations. Thes…